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Long Series of GNSS Integrated Precipitable Water as a Climate Change Indicator

机译:GNSS长系列综合可沉淀水作为气候变化指标

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This paper investigates information potential contained in tropospheric delay product for selected International GNSS Service (IGS) stations in climatologic research. Long time series of daily averaged Integrated Precipitable Water (IPW) can serve as climate indicator. The seasonal model of IPW change has been adjusted to the multi-year series (by the least square method). Author applied two modes: sinusoidal and composite (two or more oscillations). Even simple sinusoidal seasonal model (of daily IPW values series) clearly represents diversity of world climates. Residuals in periods from 10 up to 17 years are searched for some long-term IPW trend – self-evident climate change indicator. Results are ambiguous: for some stations or periods IPW trends are quite clear, the following years (or the other station) not visible. Method of fitting linear trend to IPW series does not influence considerably the value of linear trend. The results are mostly influenced by series length, completeness and data (e.g. meteorological) quality. The longer and more homogenous IPW series, the better chance to estimate the magnitude of climatologic IPW changes.
机译:本文研究了选定的国际GNSS服务(IGS)气象学对流层延迟产品中包含的信息潜力。每天平均的综合可沉淀水(IPW)的长时间序列可以用作气候指标。 IPW变化的季节性模型已调整为多年序列(通过最小二乘法)。作者应用了两种模式:正弦波和复合波(两个或多个振荡)。即使是简单的正弦季节模型(IPW每日值系列)也可以清楚地代表世界气候的多样性。在10到17年之间的残差中搜索IPW的长期趋势–不言而喻的气候变化指标。结果是模棱两可的:对于某些站点或时期,IPW趋势非常明显,接下来的几年(或其他站点)不可见。将线性趋势拟合到IPW系列的方法不会显着影响线性趋势的值。结果主要受序列长度,完整性和数据(例如气象)质量的影响。 IPW系列越长且越均匀,估计气候IPW变化幅度的机会就越大。

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